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BERTInvoiceCzechV3

Token Classification
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  1. README.md +108 -0
  2. model.safetensors +1 -1
  3. runs/Mar21_22-07-17_a922adcca173/events.out.tfevents.1774130837.a922adcca173.10208.0 +2 -2
  4. runs/Mar21_22-07-17_a922adcca173/events.out.tfevents.1774131332.a922adcca173.10208.1 +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: google-bert/bert-base-multilingual-cased
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - precision
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+ - recall
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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: BERTInvoiceCzechV3
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # BERTInvoiceCzechV3
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+
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+ This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0873
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+ - Precision: 0.8287
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+ - Recall: 0.8718
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+ - F1: 0.8497
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+ - Accuracy: 0.9790
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 0.1
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+ - num_epochs: 40
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | No log | 1.0 | 20 | 2.6840 | 0.0071 | 0.0194 | 0.0103 | 0.6810 |
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+ | No log | 2.0 | 40 | 0.6125 | 0.0 | 0.0 | 0.0 | 0.9123 |
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+ | No log | 3.0 | 60 | 0.4626 | 0.0 | 0.0 | 0.0 | 0.9123 |
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+ | No log | 4.0 | 80 | 0.3490 | 0.3419 | 0.1239 | 0.1819 | 0.9169 |
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+ | No log | 5.0 | 100 | 0.2754 | 0.3776 | 0.2893 | 0.3276 | 0.9278 |
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+ | No log | 6.0 | 120 | 0.2266 | 0.4686 | 0.4171 | 0.4413 | 0.9389 |
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+ | No log | 7.0 | 140 | 0.1828 | 0.5234 | 0.4870 | 0.5045 | 0.9466 |
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+ | No log | 8.0 | 160 | 0.1729 | 0.5567 | 0.5433 | 0.5499 | 0.9495 |
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+ | No log | 9.0 | 180 | 0.1619 | 0.5477 | 0.5577 | 0.5526 | 0.9495 |
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+ | No log | 10.0 | 200 | 0.1462 | 0.5730 | 0.5565 | 0.5646 | 0.9519 |
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+ | No log | 11.0 | 220 | 0.1457 | 0.6067 | 0.6159 | 0.6113 | 0.9531 |
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+ | No log | 12.0 | 240 | 0.1374 | 0.6406 | 0.6583 | 0.6493 | 0.9573 |
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+ | No log | 13.0 | 260 | 0.1224 | 0.6855 | 0.6882 | 0.6868 | 0.9624 |
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+ | No log | 14.0 | 280 | 0.1208 | 0.7253 | 0.7157 | 0.7205 | 0.9658 |
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+ | No log | 15.0 | 300 | 0.1127 | 0.7233 | 0.7107 | 0.7169 | 0.9656 |
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+ | No log | 16.0 | 320 | 0.1138 | 0.7535 | 0.7480 | 0.7507 | 0.9688 |
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+ | No log | 17.0 | 340 | 0.1128 | 0.7648 | 0.7639 | 0.7643 | 0.9697 |
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+ | No log | 18.0 | 360 | 0.1089 | 0.7688 | 0.7724 | 0.7706 | 0.9704 |
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+ | No log | 19.0 | 380 | 0.1033 | 0.7738 | 0.7903 | 0.7819 | 0.9707 |
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+ | No log | 20.0 | 400 | 0.0960 | 0.7982 | 0.8078 | 0.8029 | 0.9736 |
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+ | No log | 21.0 | 420 | 0.1022 | 0.7821 | 0.8252 | 0.8031 | 0.9726 |
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+ | No log | 22.0 | 440 | 0.0915 | 0.8092 | 0.8252 | 0.8172 | 0.9753 |
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+ | No log | 23.0 | 460 | 0.0901 | 0.8289 | 0.8353 | 0.8321 | 0.9773 |
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+ | No log | 24.0 | 480 | 0.0933 | 0.7954 | 0.8377 | 0.8160 | 0.9749 |
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+ | 0.3542 | 25.0 | 500 | 0.0883 | 0.8093 | 0.8388 | 0.8238 | 0.9769 |
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+ | 0.3542 | 26.0 | 520 | 0.0884 | 0.8282 | 0.8520 | 0.8400 | 0.9780 |
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+ | 0.3542 | 27.0 | 540 | 0.0898 | 0.7909 | 0.8610 | 0.8245 | 0.9757 |
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+ | 0.3542 | 28.0 | 560 | 0.0957 | 0.8004 | 0.8676 | 0.8327 | 0.9757 |
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+ | 0.3542 | 29.0 | 580 | 0.0876 | 0.8253 | 0.8548 | 0.8398 | 0.9787 |
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+ | 0.3542 | 30.0 | 600 | 0.0886 | 0.8257 | 0.8571 | 0.8411 | 0.9785 |
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+ | 0.3542 | 31.0 | 620 | 0.0867 | 0.8286 | 0.8637 | 0.8458 | 0.9792 |
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+ | 0.3542 | 32.0 | 640 | 0.0919 | 0.8132 | 0.8571 | 0.8346 | 0.9774 |
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+ | 0.3542 | 33.0 | 660 | 0.0876 | 0.8239 | 0.8668 | 0.8448 | 0.9787 |
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+ | 0.3542 | 34.0 | 680 | 0.0888 | 0.8219 | 0.8672 | 0.8439 | 0.9783 |
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+ | 0.3542 | 35.0 | 700 | 0.0872 | 0.8315 | 0.8683 | 0.8495 | 0.9792 |
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+ | 0.3542 | 36.0 | 720 | 0.0872 | 0.8287 | 0.8718 | 0.8497 | 0.9790 |
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+ | 0.3542 | 37.0 | 740 | 0.0881 | 0.8259 | 0.8715 | 0.8481 | 0.9788 |
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+ | 0.3542 | 38.0 | 760 | 0.0899 | 0.8199 | 0.8699 | 0.8442 | 0.9781 |
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+ | 0.3542 | 39.0 | 780 | 0.0892 | 0.8264 | 0.8687 | 0.8470 | 0.9786 |
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+ | 0.3542 | 40.0 | 800 | 0.0896 | 0.8246 | 0.8691 | 0.8463 | 0.9785 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 5.0.0
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+ - Pytorch 2.10.0+cu128
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.2
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